Design and scale Databricks Lakehouse architecture on AWS to support diverse data workloads
Architect, develop and maintain robust and reusable data pipelines using Databricks (PySpark/Python) for structured and unstructured data
Implement and optimize Delta Lake structures and data modeling strategies
Build and maintain CI/CD pipelines for notebooks and job workflows, support version control and automated testing
Optimize compute costs, cluster configs, and query performance across the platform
Configure and manage Unity Catalog for access control, lineage, and data security
Partner with DevOps, Cloud, and Analytics teams to align infrastructure and business needs
Act as a technical mentor to the engineering team; help with upskilling and best practices
Requirements
Deep experience with Databricks, Delta Lake, and AWS services (e.g., S3, Glue, Lambda)
5+ years of experience in data engineering, including cloud-based platforms (Preferred AWS)
Strong hands-on skills in Python, PySpark, and SQL
Experience with data orchestration and infrastructure-as-code
Understanding of data quality, performance tuning, and governance principles
Databricks Certification(s) (Preferred)
Experience integrating Databricks with enterprise data tools
Exposure to real-time data pipelines or streaming solutions
Managed Healthcare experience or knowledge of health insurance concepts, preferably Risk adjustment
Benefits
Affordable medical plan options
401(k) plan (including matching company contributions)
Employee stock purchase plan
No-cost programs for all colleagues including wellness screenings, tobacco cessation and weight management programs, confidential counseling and financial coaching
Benefit solutions that address the different needs and preferences of our colleagues including paid time off, flexible work schedules, family leave, dependent care resources, colleague assistance programs, tuition assistance, retiree medical access
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